Proceedings Article | 10 March 2006
Proc. SPIE. 6141, Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display
KEYWORDS: Tumors, Image registration, Radiofrequency ablation, Tissues, Liver, Computed tomography, Visualization, Image segmentation, Manufacturing, 3D image processing
It is fundamentally important that all cancerous cells be adequately destroyed during Radio Frequency Ablation (RFA) procedures. To help achieve this goal, probe manufacturers advise physicians to increase the treatment region by one centimeter (1cm) in all directions around the diseased tissue. This enlarged treatment region provides a buffer to insure that cancer cells that migrated into surrounding tissue are adequately treated and necrose. Even though RFA is a minimally invasive, image-guided procedure, it is difficult for physicians to confidently follow the specified treatment protocol. In this paper we visually assess an RFA treatment by comparing a registered image set containing the untreated tumor, including the 1 cm safety boundary, to that of an image set containing the treated region acquired one month after surgery. For this study, we used Computerized Tomography images as both the tumor and treated regions are visible. To align the image sets of the abdomen, we investigate three different registration techniques; an affine transform that minimizes the correlation ratio, a point (or landmark) based 3D thin-plate spline approach, and a nonlinear B-spline elastic registration methodology. We found the affine registration technique simple and easy to use because it is fully automatic. Unfortunately, this method resulted in the largest visible discrepancy between the liver in the fused images. The thin-plate spline technique required the physician to identify corresponding landmarks in both image sets, but resulted in better visual accuracy in the fused images. Finally, the non-linear, B-spline, elastic registration technique used the registration results of the thin-plate spline method as a starting point and then required a significant amount of computation to determine its transformation, but also provided the most visually accurate fused image set.
